"Information about playwrights or the Playwright framework" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
The agent-native cloud: database, functions, AI, storage, computers. 50 tools, one API key.
Ask your AI assistant a cost question. Get allocation, correlation, and explanation in one response. Costory connects Claude, Codex, or Cursor to normalized cost data across AWS, GCP, Azure, Datadog, OpenAI, and Anthropic. https://costory.io Free trial 14 days, 250 USD / month up to 10M Spend
AI infrastructure design agent. Describe your app in plain English; Riley designs, prices, and deploys AWS or GCP infrastructure with generated Terraform.
Live GPU compute & inference token price indices for AI agents — 591 reference indices across H100/A100/B200/B300 spot+on-demand, Claude/GPT/Llama token pricing, and more. Every value is methodology-versioned and citable via the /v1/verify handshake.
Render Cost Calculator: the site's own MCP server — calculator, enquiry (enquiry = a human...
Which open models fit your GPU or Mac, measured. Plus model momentum and GPU rental prices.
Compare live GPU cloud rental prices and match workloads to the cheapest provider.
Deploy HTML or dist/ to a live HTTPS URL. No account. Drop, MCP, or CLI.
Publish the website you built with AI to a live public URL — straight from chat, no setup.
Search AI capabilities across AWS Marketplace and the Official MCP Registry.
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
Hosting for AI agents: publish a live website in one tool call, ephemeral or forever.
Provision, SSH into, run commands on, and manage Linux VPSes from an AI agent. Pay USDC over x402 (Base) or by card over HTTP 402, a running box in under 60s. No signup, no API key to buy. This remote endpoint offers free browse/discovery, quotes, and server status.
Unlock the power of DNS lookups with our DNS Lookup service using Google DNS-over-HTTPS. Whether
The AWS Knowledge MCP server is a fully managed remote Model Context Protocol server that provides real-time access to official AWS content in an LLM-compatible format. It offers structured access to AWS documentation, code samples, blog posts, What's New announcements, Well-Architected best practices, and regional availability information for AWS APIs and CloudFormation resources. Key capabilities include searching and reading documentation in markdown format, getting content recommendations, listing AWS regions, and checking regional availability for services and features.
The Telnyx MCP server is an official implementation of the Model Context Protocol that enables AI clients (like Claude Desktop, Cursor, and OpenAI Agents) to interact with Telnyx's telephony, messaging, and AI assistant APIs. It provides comprehensive capabilities including making and managing phone calls, sending SMS/MMS messages, purchasing and configuring phone numbers, creating AI assistants with custom instructions, managing cloud storage buckets, scraping and embedding website content, and handling integration secrets. The server exists as both a local implementation and a remotely hosted version, allowing developers to integrate real-world communication infrastructure directly into AI applications.
The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.
AI first app deployment, unlike lovable or figma make, webslop.ai lets you or your ai of choice setup node.js apps or static sites in seconds. Designed be be the perfect place for you to deploy websites and apps super fast to the rest of the world and has a generous free tier.
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
The Google Compute Engine MCP server is a fully-managed Model Context Protocol server that provides tools to manage Google Compute Engine resources through AI agents. It enables capabilities including instance management (creating, starting, stopping, resetting, listing), disk management, handling instance templates and group managers, viewing machine and accelerator types, managing images, and accessing reservation and commitment information. The server operates as a zero-deployment, enterprise-grade endpoint at https://compute.googleapis.com/mcp with built-in IAM-based security.
